Advanced Manufacturing Technologies and Machine Learning in Unmanned Aviation Systems

ABSTRACT

A vehicle can be configured to include a body having a body bottom conjoined with a body sidewall and a body top forming a body cavity. The body top includes a body top opening and the body sidewall includes a body sidewall opening. The vehicle can include a payload housing having a payload bottom conjoined with a payload housing sidewall and a payload housing top forming a payload housing cavity, wherein the payload housing cavity is configured to hold at least one operating module for the vehicle. The vehicle can include at least one arm. The vehicle can include at least one interlocking arrangement of the body top opening or body side wall configured to removably secure the payload housing and the at least one arm to the body. Each of the body, the payload housing, and the at least one arm can be structured with additive manufactured material.

FIELD

Embodiments relate to a vehicle composed of additive manufactured partsconfigured to be assembled in a tool-less fashion. The vehicle caninclude an operating module configured to function as a surveillancesystem that identifies objects within an environment and to reduce thedata bandwidth that would otherwise be needed to transmit data from thevehicle to another device. The operating module can be configured totransmit object coordinates with object recognition information as partof the data being transmitted to the other device.

BACKGROUND INFORMATION

Known unmanned vehicles and reconnaissance systems are limited in thatthey are designed to operate in a single operational mode. There is nomeans to configure and re-configure the vehicle to meet differentoperational criteria. Known vehicles and systems do not provide avehicle platform made of modular components that can be assembled anddis-assembled for re-configuration in a simple and efficient manner. Inaddition, known systems rely on transmitting full video streams from thevehicle to a receiver, which requires significant data bandwidth.

SUMMARY

Embodiments can relate to a vehicle having a body bottom conjoined witha body sidewall and a body top forming a body cavity, wherein the bodytop includes a body top opening and the body sidewall includes a bodysidewall opening. The vehicle can include a payload housing having apayload bottom conjoined with a payload housing sidewall and a payloadhousing top forming a payload housing cavity, wherein the payloadhousing cavity is configured to hold at least one operating module forthe vehicle. The vehicle can include at least one arm. The vehicle caninclude at least one interlocking arrangement of the body top opening orbody side wall configured to removably secure the payload housing andthe at least one arm to the body. Each of the body, the payload housing,and the at least one arm can be structured with additive manufacturedmaterial.

Embodiments can relate to a method of using a vehicle. The method ofusing a vehicle can involve manually assembling a payload housing and atleast one arm to a body via at least one interlocking arrangement usedto secure the payload housing to the body, and the at least one arm tothe body. The method of using a vehicle can involve manually attachingat least one motor to the at least one arm.

Embodiments can relate to an operating module for a vehicle, theoperating module having a navigation module including a navigationprocessor and a navigation sensor, the navigation module configured tocommunicate with at least one motor of the vehicle to facilitatenavigation and propulsion of the vehicle. The operating module caninclude a surveillance module including a surveillance processor and asurveillance sensor, the surveillance module configured to: receive rawdata, the raw data including real time video stream information about anenvironment; and generate distilled data, the distilled data includingstill image information from the real time video stream information, thestill image information including at least one object identified via anobject classification and localization technique. The operating modulecan include a telemetry module including a telemetry processor and atelemetry transceiver, the telemetry module configured to transmit thedistilled data to a computer device.

Embodiments can relate to a method of surveillance involving receivingraw data at a first data bandwidth, the raw data including real timevideo stream information about an environment. The method ofsurveillance can involve generating distilled data, the distilled dataincluding still image information from the real time video streaminformation, the still image information including at least one objectidentified via an object classification and localization technique. Themethod of surveillance can involve transmitting the distilled data at asecond data bandwidth, the first data bandwidth being greater than thesecond data bandwidth.

Embodiments can relate to an operating module for a vehicle, theoperating module having a navigation module including a navigationprocessor and a navigation sensor, the navigation module configured tocommunicate with a motor of the vehicle for navigation and propulsion ofthe vehicle. The operating module can include a surveillance moduleincluding a surveillance processor and a surveillance sensor, thesurveillance module configured to: receive raw data, the raw dataincluding real time video stream information about an environment; andprocess the raw data to generate distilled data, the distilled dataincluding a still image information from the real time video streaminformation, the still image information including at least one objectidentified via an object classification and localization technique. Theoperating module can include a telemetry module including a telemetryprocessor and a telemetry transceiver, the telemetry module configuredto transmit the distilled data to a computer device. The navigationmodule can generate vehicle coordinates and the surveillance module canuse the vehicle coordinates and a ranging technique to generate objectcoordinates for the at least one object. The surveillance module canco-register the object coordinates with the at least one object andinclude the co-register object coordinates as part of the distilleddata.

Embodiments can relate to a method of surveillance involving receivingraw data at a first data bandwidth, the raw data including real timevideo stream information about an environment. The method ofsurveillance can involve generating distilled data from the raw data,the distilled data including a still image information from the realtime video stream information, the still image information including atleast one object identified via an object classification andlocalization technique. The method of surveillance can involveco-registering object coordinates for the at least one identified objectas part of the distilled data. The method of surveillance can involvetransmitting distilled data at a second data bandwidth.

Embodiments can relate to a vehicle having a body including at least onemount, each mount configured to secure a motor. The vehicle can have apayload including at least one operating module for the vehicle. Thevehicle can have at least one interlocking arrangement configured toremovably secure the payload to the body. The body can be structuredwith additive manufactured material.

Embodiments can relate to a method of producing a vehicle involvinggenerating a body via additive manufacturing. The method can involve andgenerating a payload including at least one operating module for thevehicle. At least one interlocking arrangement can be included in or onthe body and configured to removably secure the payload to the body bymanual assembly.

BRIEF DESCRIPTION OF THE DRAWINGS

Other features and advantages of the present disclosure will become moreapparent upon reading the following detailed description in conjunctionwith the accompanying drawings, wherein like elements are designated bylike numerals, and wherein:

FIG. 1 shows an exemplary embodiment of the vehicle;

FIG. 2 shows an exemplary embodiment of the vehicle as an exploded viewof exemplary component parts of the vehicle;

FIG. 3 shows an exemplary embodiment of the body portion of anembodiment of the vehicle;

FIG. 4 shows an exemplary embodiment of the payload housing portion ofan embodiment of the vehicle;

FIG. 5 shows an exemplary embodiment of the cover portion of anembodiment of the vehicle;

FIG. 6 shows an exemplary embodiment of the arm portion of an embodimentof the vehicle;

FIG. 7 shows an exemplary embodiment of the interlocking arrangementportion of an embodiment of the vehicle;

FIG. 8 shows an embodiment of the vehicle configured as an aerialvehicle;

FIG. 9 shows exemplary component parts of an embodiment of the vehicleconfigured as an aerial vehicle;

FIG. 10 shows an exemplary Finite Element Analysis used to designcomponent parts of an embodiment of the vehicle;

FIG. 11 shows an exemplary system schematic for an embodiment of thevehicle;

FIG. 12 shows an exemplary wiring diagram for an embodiment of thevehicle;

FIG. 13 shows exemplary module architectures for an embodiment of thevehicle;

FIG. 14 shows an exemplary motor connections set-up for an embodiment ofthe vehicle;

FIG. 15 shows exemplary navigation or avionics module wiring for anembodiment of the vehicle;

FIG. 16 shows exemplary surveillance module wiring for an embodiment ofthe vehicle;

FIG. 17 shows an exemplary communications system architecture that canbe used for an embodiment of the vehicle;

FIG. 18 shows exemplary still image information that can be used as partof the distilled data for an embodiment of the vehicle; and

FIG. 19 shows exemplary still image information that can be used as partof the distilled data for an embodiment of the vehicle.

DETAILED DESCRIPTION

Embodiments can include a vehicle 100 (e.g., unmanned vehicle) composedof additive manufactured parts configured to be assembled in a tool-lessfashion. It is contemplated for the vehicle 100 to be an unmannedvehicle and used for surveillance or reconnaissance. Surveillance andreconnaissance can involve receiving data regarding an environment,processing the data, and transmitting the data to a computer device 1712for review or further analysis or further processing. The vehicle 100can include an operating module 202 configured to reduce the databandwidth that would otherwise be needed to transmit data (e.g.,surveillance data) from the vehicle 100 to another device (e.g.,computer device 1712). The operating module 202 can be configured totransmit object coordinates with object recognition information as partof the data being transmitted to the computer device 1712. Thesurveillance and reconnaissance can involve receiving data about objectswithin the environment. For instance, the vehicle 100 can be used forsurveillance and reconnaissance of an area of operation (AOO) or area ofinterest (AOI) identified by military personnel, police personnel,emergency or first responders, researchers, scientists, investigators,explorers, enthusiasts etc. The vehicle 100 can be used to identify andtrack personnel or objects in the AOO or AOI, identify and trackphenomenon (e.g., weather events, geological events, etc.), hazardousconditions, etc. The vehicle 100 can be operated remotely by a user, canbe operated autonomously, or can be operated semi-autonomously. It isalso contemplated for the vehicle 100 to be transportable by a singleperson with ease and to be assembled, dis-assembled, and/orre-configured with minimal effort and without the use of tools.

Embodiments of the vehicle 100 can be structured so as to allow thevehicle 100 to be expendable. For instance, the vehicle 100 can be usedto carry out a surveillance and reconnaissance task, and then be allowedto self-destruct, crash, or remain in the AOO or AOI without returning.This can be achieved by the specific configuration of component parts(e.g., the body 102, the payload housing 200, the arm 104, etc.) andmethods for implementation that allow for the construction of a reliableand effective vehicle 100 at a low cost and with the use of minimalresources.

Embodiments of the vehicle 100 can be structured so that the componentparts are assembled in a modular fashion. This can allow the vehicle 100to be configured and re-configured by a user and on-the-fly to meetspecific design criteria or perform a specific type of surveillance andreconnaissance. In addition, components of the vehicle 100 can be easilyreplaced and/or manufactured with the use of additive manufacturingmachines. This further leads to the reliability, versatility, andexpendability of the vehicle.

With reference to FIGS. 1-7, embodiments of the vehicle 100 will bedescribed and illustrated.

An embodiment of the vehicle 100 can include a body 102 having a bodybottom 304 conjoined with a body sidewall 302 and a body top 300 forminga body cavity 306, wherein the body top 300 includes a body top opening310 and the body sidewall 302 includes a body sidewall opening 312. Thebody 102 is shown to be rectangular cuboidal, but the body 102 can bemade into other shapes. These can be, but are not limited to, cubic,spherical, pyramidal, disc-shaped, etc. Embodiments of the vehicle 100can be an aerial vehicle, a land vehicle, and/or a water vehicle. Theshape of the vehicle 100 may depend on the intended use so as to allowthe vehicle 100 to better fly in the atmosphere, traverse the terrain,or propel in or on water. The body cavity 306 can be configured toslidably receive and retain at least one operating module 202 for thevehicle 100. Thus, the body 102 can be structured as a carriage for thevehicle 100 and a frame for the operating module 202. It is contemplatedfor the operating module 202 to generate heat when in operation so thebody 102 (e.g. the body bottom 304 and/or the body sidewall 302) canhave, at least one aperture 314 or vent to facilitate heat transfer fromthe operating module 202 to an area outside of the body cavity 306.

In addition to the heat transfer apertures 314, any component of thevehicle 100 can include apertures formed therein to lighten the weightof the vehicle 100 without degrading structural integrity of thatcomponent. In addition, any component of the vehicle 100 can includestructural formations (e.g., ridges, grooves, flutes, web-formations,etc.) to improve the structural rigidity or other mechanical property ofthe component.

The vehicle 100 can include a payload housing 200 having a payloadbottom 406 conjoined with a payload housing sidewall 402 and a payloadhousing top 400 forming a payload housing cavity 408, wherein thepayload housing cavity 408 is configured to hold at least one operatingmodule 202 for the vehicle 100. The payload housing 200 can beconfigured to slidably insert into the body cavity 306. Thus, thepayload housing 200 can have a shape that matches or complements that ofthe body cavity 306. For instance, the body cavity 306 can berectangular cuboidal and the payload housing 200 can be rectangularcuboidal but of slightly smaller dimensions so as to allow the payloadhousing 200 to slidably insert within the body cavity 306. Other shapesfor the payload housing 200 can be used. While the exemplary embodimentsshow the body cavity 306 having a shape that matches that of the payloadhousing 200, it does not have to. Instead, the body cavity 306 can havea shape and dimensions that accommodates the shape and dimensions of thepayload housing 200 without matching that of the payload housing 200.

The body 102 can have a body top opening 310 to allow for the slidableinsertion and removal of the payload housing 200. In addition, or in thealternative, the body sidewall 302 can also have a body sidewall opening312 for the same. Similarly, any portion of the payload housing 200 canhave an opening to facilitate insertion and removal of at least oneoperating module 202, sensor, processor, and/or other element of thepayload (the payload being an element that is contained by the payloadhousing 200).

The vehicle 100 can include at least one arm 104. The arm 104 can be astructure that supports the body 102. For example, for a land vehicle100, the arm(s) 104 can serve as a wheeled-axle to support the body 102thereon. The arm(s) 104 can be a structure that supports the means forpropulsion. In this regard, the arm(s) 104 can be used in accordancewith the method of propulsion. For instance, for a water vehicle 100,the arm(s) 104 can serve as a rudder, a structural support for apropeller or thruster, etc. For an aerial vehicle 100, the arm(s) 104can serve as a structural support for a propeller 802.

Exemplary embodiments show the vehicle 100 configured as an unmannedaerial vehicle 100 or a drone. The arm 104 is used to provide astructural support for a rotatable motor 110. The rotatable motor 110has a spindle 114 to facilitate connection to a propeller 802. When thearm 104 is attached to the body 102, the spindle 114 extends in alongitudinal direction 116 so as to allow the propeller 802 to be normal(or substantially normal) to the longitudinal direction 116.

The arm 104 can be configured to removably attach to a portion of thebody 102. In the exemplary embodiment shown in FIG. 6, the arm 104 has atriangular shape, having a first side 316, a second side 318, and athird side 320 with an open center 600. For example, the arm 104 can bein the shape of a as a right triangle with the first side 316 being theopposite side, the second side 318 being the adjacent side, and thethird side 320 being the hypotenuse. The junction of the second side 318and the third side 320 can include a mount 112. The mount 112 can beconfigured to receive the rotatable motor 110. The first side 316 can bestructured to have an interlocking arrangement 308 that will facilitatethe removable attachment of the arm 104 to the body 102.

Some embodiments can include at least one interlocking arrangement 308on the body top opening 310 or body sidewall 302 configured to removablysecure the payload housing 200 and the at least one arm 104 to the body102. It is contemplated for the components of the vehicle 100 to beremovably attachable to each other. This can be achieved via at leastone interlocking arrangement 308. The interlocking arrangement 308 canbe a snap-fit, interference fit, a tessellation engagement, arail-and-guide engagement, etc.

For instance, the body 102 can have a body inner surface 322 and a bodyouter surface 324. The body inner surface 322 can have a guide 700and/or rail 702 formed therein. The guide 700 and/or rail 702 can be inthe longitudinal direction 116 and/or latitudinal direction 118. Thepayload housing 200 can have a payload housing inner surface 410 and apayload housing outer surface 412. The payload housing outer surface 412can have a rail 702 and/or guide 700 formed therein. The rail 702 and/orguide 700 can be in the longitudinal direction 116 and/or latitudinaldirection 118. Each rail 702 or guide 700 of the payload housing 200 canbe configured to engage with each guide 700 or rail 702 of the body 102to allow the payload housing 200 to be slidably inserted into the bodycavity 306 of the body 102 and be secured in place. It is contemplatedfor the rail 702 to slide into the space of the guide 700 so as togenerate a snug fit. Thus, the cross-sectional shape of the rail 702 canmatch or complement that of the guide 700 it is being slid into. Thecross-sectional shape of the rail 702 and/or guide 700 can be square,arcuate, triangular, keystone, T-shaped, etc. The snug fit can begenerated by the tight tolerance of the rail 702 and guide 700dimensions, an interference snap connection, etc.

In addition, the body outer surface 324 can have a guide 700 and/or rail702 formed therein. The guide 700 and/or rail 702 can be in thelongitudinal direction 116 and/or latitudinal direction 118. The firstside 316 of the arm 104 can have a rail 702 and/or guide 700 formedtherein. The rail 702 and/or guide 700 can be in the longitudinaldirection 116 and/or latitudinal direction 118. Each rail 702 or guide700 of the arm 104 can be configured to engage with each guide 700 orrail 702 of the body 102 to allow the arm 104 to be slidably connectedto the body 102 and be secured in place. It is contemplated for the rail702 to slide into the space of the guide 700 so as to generate a snugfit. Thus, the cross-sectional shape of the rail 702 can match orcomplement that of the guide 700 it is being slid into. Thecross-sectional shape of the rail 702 and/or guide 700 can be square,arcuate, triangular, keystone, T-shaped, etc. The snug fit can begenerated by the tight tolerance of the rail 702 and guide 700dimensions, an interference snap connection, etc.

In some embodiments, each of the body 102, the payload housing 200, andthe at least one arm 104 are structured with additive manufacturedmaterial. This can be metal, metal alloy, composite material, plastic,polymer, etc. It is contemplated for any one or combination ofcomponents of the vehicle 100 to be produced using additivemanufacturing. This can allow a user to fabricate a component as-needed,provided the user has access to an additive manufacturing apparatus1714. The additive manufacturing apparatus 1714 can be an apparatusconfigured to deposit a binder material onto a powder bed to generate abuild layer by layer via Binder Jetting or Selective Laser Sinteringmethods. Other additive manufacturing techniques can include FusedDeposition Modeling, Stereolithography, Digital Light Processing,Selective Laser melting, Electron Beam Melting, etc. The additivemanufacturing apparatus 1714 can include a processing unit configured tooperate via a build file that has the necessary instructions forgenerating the build. The build can be a component part of the vehicle100.

The ability to: 1) fabricate a component as-needed with use of anadditive manufacturing apparatus 1714; and 2) the ability to configureand re-configure the vehicle 100 on-the-fly to meet specific designcriteria or perform a specific type of surveillance and reconnaissanceby the modularity of the component parts is based in part on thespecific design and system criteria imposed on the shapes andconfigurations of the component parts. In this regard, embodiments ofthe method of using the vehicle 100 can involve developing the buildfile for the additive manufacturing apparatus 1714 via Finite ElementAnalysis (“FEA”). (See FIG. 10). A build file can be generated for eachcomponent of the vehicle 100 and either stored on a memory of theadditive manufacturing apparatus 1714 or transferred thereto.Embodiments of the method can involve use of FEA to set the parametersof the build file that will control product characteristics for thecomponent part by generating operational parameters to control theadditive manufacturing apparatus 1714 and predictively optimizing themto meet design requirements. FEA can also be used to take into accountdesired material and mechanical characteristics and other parametersthat enable the component part to be made via additive manufacturing andto function properly during subsequent use as a surveillance andreconnaissance vehicle 100. For example, material properties, mechanicalproperties, use of least amount of material, structural integrity,reduction of weight, transfer of moments and force vectors, etc. can bemathematically modeled and represented by variables during the FEA.Algorithmic functions including use of these variables can then begenerated and incorporated into the build file. The build file can thenbe operated on a processor of the additive manufacturing apparatus 1714to develop a design for the component part.

For example, a user can input at least one variable into the additivemanufacturing apparatus 1714, such as the dimensions and desired weightof the component part to be produced. The processor of the additivemanufacturing apparatus 1714 can then run at least one algorithmembedded in the build file to generate at least one the operatingparameter that would generate a component part exhibiting the desiredcharacteristics. In some embodiments, the additive manufacturingapparatus 1714 can be programmed (via the build file) to generate aplurality of operating parameters as a function of another operatingparameter. For example, the additive manufacturing apparatus 1714 maygenerate a set of operating parameters for each powdered materialavailable to a user that would result in a component part having thedimensions, shapes, locations of interlocking arrangements, etc. thatwould provide the desired mechanical properties (e.g., the ability forit to be fabricated via additive manufacturing, the ability for it toinclude and use the interlocking arrangements for assembly anddisassembly, etc.). A user may then select the powdered material (orother raw material, based on the method of additive manufacturing used)with the most desirable characteristics to be used by the additivemanufacturing apparatus 1714 to make the component. The ability to makethe component parts via additive manufacturing can obviate the need fora user to have to carry all of the component parts that he or she wouldconceivably need.

In some embodiments, each of the body 102, the payload housing 200, andthe at least one arm 104 are structured entirely with additivemanufactured material. Embodiments of the vehicle 100 can be configuredso that each component can be produced via additive manufacturing. Thiscan provide a user the ability to fabricate any component as-needed sothat the user does not have to carry spare parts or parts that would beneeded for re-configuration with him or her. Instead, the user merelyfabricates the part on the spot.

The vehicle can include a cover 106 structured with additivemanufactured material, wherein the at least one interlocking arrangement308 is configured to removably secure the cover 106 to the body 102. Thebody outer surface 324 can have a guide 700 and/or rail 702 formedtherein. The guide 700 and/or rail 702 can be in the longitudinaldirection 116 and/or latitudinal direction 118. The cover 106 can have acover outer surface 500 and a cover inner surface 502. The cover innersurface 502 can have a rail 702 and/or guide 700 formed therein. Therail 702 and/or guide 700 can be in the longitudinal direction 116and/or latitudinal direction 118. Each rail 702 or guide 700 of thecover 106 can be configured to engage with each guide 700 or rail 702 ofthe body 102 to allow the cover 106 to be slidably connected to the body102 and be secured in place. It is contemplated for the rail 702 toslide into the space of the guide 700 so as to generate a snug fit.Thus, the cross-sectional shape of the rail 702 can match or complementthat of the guide 700 it is being slid into. The cross-sectional shapeof the rail 702 and/or guide 700 can be square, arcuate, triangular,keystone, T-shaped, etc. The snug fit can be generated by the tighttolerance of the rail 702 and guide 700 dimensions, an interference snapconnection, etc. It is contemplated for the cover 106 to be secured tothe body 102 at the body top opening 310 so as to be placed over thebody top opening 310. The cover 106 can be used to cover, conceal,and/or protect the contents (e.g., the payload housing 200, theoperating module 202, etc.) placed within the body cavity 306.

In some embodiments, the at least one interlocking arrangement 308 isconfigured to be manually transitioned between an engaged configurationand a disengaged configuration. Any of the interlocking arrangements 308described herein can be transitioned to and from an engagedconfiguration (e.g., the rail 702 being snugly fit within the guide 700)and a disengaged configuration (e.g., the rail 702 being removed fromthe guide 700). This transition can be done manually (e.g., without theuse of tools or other equipment). The overall vehicle 100 structure, theshapes and configurations of the component parts, and the placement andconfiguration of the interlocking arrangements 308 can be specificallydesigned via FEA or other analytical methods to allow for this manualengagement and disengagement but to also provide a vehicle 100 that willoperate and function effectively and reliably. Known vehicles cannot beassembled without the use of tools for assembly, and if their partswould be configured to be assembled without the use of tools then itwould lead to a significant degradation in performance.

In some embodiments, the at least one arm 104 includes plural arms. Inan exemplary embodiment, the vehicle 100 is configured as an unmanned,aerial vehicle that operates like a drone. In this regard, the vehicle100 can include four arms 104, each arm having a propeller 802 toprovide lift and thrust so that the vehicle 100 can operate as ahelicopter style rotocraft. For instance, the vehicle 100 can have afirst arm 104, a second arm 104, a third arm 104, and a fourth arm 104.The first arm 104 can have a triangular shape, having a first side 316,a second side 318, and a third side 320 with an open center. Thejunction of the second side 318 and the third side 320 can include amount 112. The mount 112 can be configured to receive the rotatablemotor 110. The first side 316 can be structured to have an interlockingarrangement 308 that will facilitate the removable attachment of the arm104 to the body 102. The second arm 104 can have a triangular shape,having a first side 316, a second side 318, and a third side 320 with anopen center. The junction of the second side 318 and the third side 320can include a mount 112. The mount 112 can be configured to receive therotatable motor 110. The first side 316 can be structured to have aninterlocking arrangement 308 that will facilitate the removableattachment of the arm 104 to the body 102. The third arm 104 can have atriangular shape, having a first side 316, a second side 318, and athird side 320 with an open center. The junction of the second side 318and the third side 320 can include a mount 112. The mount 112 can beconfigured to receive the rotatable motor 110. The first side 316 can bestructured to have an interlocking arrangement 308 that will facilitatethe removable attachment of the arm 104 to the body 102. The fourth arm104 can have a triangular shape, having a first side 316, a second side318, and a third side 320 with an open center. The junction of thesecond side 318 and the third side 320 can include a mount 112. Themount 112 can be configured to receive the rotatable motor 110. Thefirst side 316 can be structured to have an interlocking arrangement 308that will facilitate the removable attachment of the arm 104 to the body102. Each arm 104 can be connected to the body 102 via interlockingarrangements 308 located at or near the corners 120 of a rectangularcuboidal shaped body 102. For instance, the first arm 104 can beconnected to a first corner 120 via a first interlocking arrangement308, the second arm 104 can be connected to a second corner 120 via asecond interlocking arrangement 308, the third arm 104 can be connectedto a third corner 120 via a third interlocking arrangement 308, and thefourth arm 104 can be connected to a fourth corner 120 via a fourthinterlocking arrangement 308.

In some embodiments, the at least one arm 104 includes a failure pointconfigured to facilitate mechanical failure of the at least one arm 104upon experiencing a threshold force vector before transferring thethreshold force vector to another component of the vehicle 100. Forinstance, when the arm 104 is connected to the body 102, the arm 104 canbe configured to fail when a threshold force vector is applied to thearm 104 before the arm 104 transfers the threshold force vector to thebody 102.

In some embodiments, the at least one arm 104 includes a motor 110configured to propel the vehicle 100. As noted herein, the arm 104 caninclude a mount 112 configured to receive the motor 110. The motor 110can be an electric rotable motor with a spindle 114 extending therefromto facilitate connection of a propeller 802 thereto. An exemplary motor110 can be an AX-2810Q-750 KV Brushless Quadcopter Motor, but othermotors can be used. The connection of the propeller 802 to the spindle114 can be via an interlocking arrangement 308. The motor 110 can beconfigured to be secured to the mount 112 via a thumb-screw engagement.The motor 110 can include a gimbal assembly to allow for adjustment ofpitch, roll, and/or yaw of the propeller 802 and/or the vehicle 100itself.

In some embodiments, the at least one arm 104 includes an electricalconnector conduit 108 configured to route an electrical connector 800from the motor 110 to facilitate electrical communication between themotor 110 and the at least one operating module 202. For instance, thesecond side 318 can include a channel or duct running along at least aportion of the second side 318 as the conduit 108 to allow routing anelectrical connector 800. The electrical connector 800 can be electricalwiring, terminals, adapters, plugs, sockets, etc. that can facilitateelectrical communication between the motor 110 and the operating module202 or an element of the operating module 202. For instance, the firstarm 104 can include an electrical connector conduit 108 along its secondside 318 to facilitate routing an electrical connector 800 from themotor 110 of the first arm 104 to the operating module 202, the secondarm 104 can include an electrical connector conduit 108 along its secondside 318 to facilitate routing an electrical connector 800 from themotor 110 of the second arm 104 to the operating module 202, the thirdarm 104 can include an electrical connector conduit 108 along its secondside 318 to facilitate routing an electrical connector 800 from themotor 110 of the third arm 104 to the operating module 202, and thefourth arm 104 can include an electrical connector conduit 108 along itssecond side 318 to facilitate routing an electrical connector 800 fromthe motor 110 of the fourth arm 104 to the operating module 202.

Referring to FIGS. 8-9, the vehicle 100 can be configured to be anaerial vehicle, a land vehicle, and/or a water vehicle. In this regard,the method of propulsion can be tailored to accommodate the type ofvehicle 100. For instance, the motor(s) 110 for the aerial vehicle maybe configured to drive the propellers 802, the motor(s) 110 for a landvehicle may be configured to drive the wheel(s), the motor(s) 110 forthe water vehicle may be configured to drive the propellers orthrusters, etc. The shape and dimensions of the component parts, thetype and location of the interlocking arrangements 308, the selection ofthe materials used for fabrication, etc. can be designed via finiteelement analyses or other analytics disclosed herein to meet the designcriteria that will enable the vehicle 100 to operate as an aerial, land,or water vehicle while still meeting the criterial of: 1) having modularcomponents; 2) being assembled and disassembled without the use oftools; and 3) having each component being able to be fabricated viaadditive manufacturing.

The vehicle 100 can be configured to be an autonomous vehicle.Embodiments of the vehicle 100 can be configured to operateautonomously, but can also be configured to operate manually (e.g., viaremote control) and/or semi-autonomously. This can be achieved via theuse of any one or combination of a navigation module 1102, asurveillance module 1100, and a telemetry module 1104 as part of theoperating module 202.

Referring to FIG. 11, in some embodiments, the at least one operatingmodule 202 includes a navigation module 1102, a surveillance module1100, and/or a telemetry module 1104. Other types of operating modules202 can be used. These can include, but are not limited to a deliverymodule, a mapping module, a scanning module, a tracking module, astorm-chasing module, photography module, wi-fi hotspot module,telemetry booster module, an advertising module, etc. The navigationmodule 1102 can include a navigation processor 1110 and a navigationsensor 1112. The navigation module 1102 can be configured to communicatewith at least one motor 110 of the vehicle 100 to facilitate navigationand propulsion of the vehicle 100. The surveillance module 1100 caninclude a surveillance processor 1106 and a surveillance sensor 1108.The surveillance module 1100 can be configured to receive raw data 1700and generate distilled data 1702. The telemetry module 1104 can includea telemetry processor 1114 and a telemetry transceiver 1116. Thetelemetry module 1104 can be configured to transmit the distilled data1702 to a computer device 1712.

Any of the processors disclosed herein can be at least a one of ascalable processor, parallelizable processor, and optimized formulti-thread processing capabilities. In some embodiments, the processorcan be a graphics processing unit (GPU). The processor can include anyintegrated circuit or other electronic device (or collection of devices)capable of performing an operation on at least one instructionincluding, without limitation, Reduced Instruction Set Core (RISC)processors, CISC microprocessors, Microcontroller Units (MCUs),CISC-based Central Processing Units (CPUs), and Digital SignalProcessors (DSPs). The hardware of such devices may be integrated onto asingle substrate (e.g., silicon “die”), or distributed among two or moresubstrates. Various functional aspects of the processor may beimplemented solely as software or firmware associated with the processor

Any of the processors disclosed herein can be optionally associated witha memory. Embodiments of the memory can include a volatile memory store(such as RAM), non-volatile memory store (such as ROM, flash memory,etc.) or some combination of the two. For instance, the memory caninclude, but is not limited to, RAM, ROM, EEPROM, flash memory or othermemory technology CDROM, digital versatile disks (DVD) or other opticalstorage, magnetic cassettes, magnetic tape, magnetic disk storage orother magnetic storage devices, or any other medium which can be used tostore the desired information and which can accessed by the processor.According to exemplary embodiments, the memory can be a non-transitorycomputer-readable medium. The term “computer-readable medium” (or“machine-readable medium”) as used herein is an extensible term thatrefers to any medium or any memory, that participates in providinginstructions to the processor for execution, or any mechanism forstoring or transmitting information in a form readable by a machine(e.g., a computer). Such a medium may store computer-executableinstructions to be executed by a processing element and/or controllogic, and data which is manipulated by a processing element and/orcontrol logic, and may take many forms, including but not limited to,non-volatile medium, volatile medium, and transmission media.

Transmission media includes coaxial cables, copper wire and fiberoptics, including the wires that include or form a bus. Transmissionmedia can also take the form of acoustic or light waves, such as thosegenerated during radio-wave and infrared data communications, or otherform of propagated signals (e.g., carrier waves, infrared signals,digital signals, etc.). Forms of computer-readable media include, forexample, a floppy disk, a flexible disk, hard disk, magnetic tape, orany other magnetic medium, a CD-ROM, any other optical medium,punch-cards, paper-tape, any other physical medium with patterns ofholes, a RAM, a PROM, and EPROM, a FLASH-EPROM, any other memory chip orcartridge, a carrier wave as described hereinafter, or any other mediumfrom which a computer can read.

Instructions for implementation of any of the methods disclosed hereincan be stored on the memory in the form of computer program code. Thecomputer program code can include program logic, control logic, or otheralgorithms that may or may not be based on artificial intelligence(e.g., machine learning techniques, artificial neural networktechniques, etc.).

The navigation module 1102 can be an avionics module. For instance, thenavigation module 1102 can include a navigation processor 1110 and anavigation sensor 1112 that will allow the operating module 202 toautonomously or semi-autonomously control the motors 110 (and thus thepropellers 802) of the vehicle 100 to allow the vehicle 100 take-off,fly, navigate through an aerial space, and land. This can includecontrolling the lift, thrust, pitch, roll, and/or yaw vehicle 100.

A method of using a vehicle 100 can involve manually assembling apayload housing 200 and at least one arm 104 to a body 102 via at leastinterlocking arrangement 308 used to secure the payload housing 200 tothe body 102 and the at least one arm 104 to the body 102. For instance,the payload housing 200 can be inserted within the body cavity 306 andsecured in place via at least one interlocking arrangement 308. Thepayload housing 200 can have at least one operating module 202 securedwithin the payload housing cavity 408. The first, second, third, andfourth arms 104 can be attached to the body 102 via additionalinterlocking arrangements 308.

The method of using a vehicle 100 can involve manually attaching atleast one motor 110 to the at least one arm 104. For instance, a firstmotor 110 can be secured to the first mount 112 of the first arm 104 viaa thumb-screw engagement, a second motor 110 can be secured to thesecond mount 112 of the second arm 104 via a thumb-screw engagement, athird motor 110 can be secured to the third mount 112 of the third arm104 via a thumb-screw engagement, and a fourth motor 110 can be securedto the fourth mount 112 of the fourth arm 104 via a thumb-screwengagement. An individual propeller 802 can be secured to eachindividual motor 110 (e.g., the vehicle XX can have four propellers 802for the four motors 110). An electrical connector 800 for each arm 104can be routed from the motor 110 of that arm 104 via the electricalconnector conduit 108 to facilitate electrical communication between themotor 110 and the at least one operating module 202.

In some embodiments, the method of using the vehicle 100 can involvefabricating the body 102, the payload housing 200, and the at least onearm 104 via additive manufacturing. This can involve fabricating thebody 102, the payload housing 200, and the at least one arm 104 usingthe additive manufacturing apparatus 1714.

In some embodiments, the method of using a vehicle 100 can involvereceiving raw data 1700 including real time video stream informationabout an environment 1718, and generating distilled data 1702 includingstill image information from the real time video stream information, thestill image information including at least one object 1716 identifiedvia an object classification and localization technique. Embodiments ofthe surveillance module 1100 can include a surveillance sensor 1108. Thesurveillance sensor 1108 can be a camera (e.g., optical camera, digitalcamera, infrared camera, or other camera operating in another spectrum,etc.). The camera can be configured to record real time video streaminformation about the environment 1718. Embodiments of the surveillancemodule 1100 can include a surveillance processor 1106. The surveillancesensor 1108 can include other sensors, such as light detection andranging sensors, sound sensors, Global Positioning System (GPS) antenna,optical flow sensors configured to track movement of objects, chemicalsensors, biological sensors, radiological sensors, nuclear sensors,ultraviolet light sensors, particulate matter sensors, emissionssensors, etc. The surveillance processor 1106 can be configured toreceive and process the real time video stream information and generatestill image information therefrom. The still image information can be aportion or segment of the real time video stream, a compilation ofplural portions or segments of the real time video stream, etc. Forinstance, the still image information can be an image or a file that isrepresentative of the environment 1718 or a portion of the environment1718 in a form that can be displayed, printed out (e.g., a virtualprintout forming a file of the image), or processed further. The stillimage information can include additional information about theenvironment 1718, such as identification of at least one object 1716 inthe environment 1718 for example. This can be achieved by thesurveillance processor 1106 executing an object classification andlocalization technique. The additional information can be superimposedon the image of the environment 1718 and/or displayed in juxtapositionwith the image of the environment 1718.

In some embodiments, the raw data 1700 can include location data (e.g.,data received by a GPS when available). It may also include other dataacross the electromagnetic spectrum, which may include but is notlimited to infrared, radio, laser reflection for objecttargeting/range/position, data from optical flow sensors to detectmovement over a reference surface (ground, rooftops, etc.),chemical/biological sensors, and/or other environmental data dependingon the payload selected. In some embodiments, the distilled data 1702can include position (longitude, latitude, and altitude of object 1716)and can be presented in Military Grid Reference System MGRS coordinates,or presented via other positioning systems (e.g., WGS 84 globalreference system, NAD 83 geodetic datum network, etc.) to reportposition on and/or over the ground. The distilled data 1702 can alsoinclude thermal signature information, time reference information,apparent motion of an object 1716 of interest, chemical/biological orother environmental and particulate information, etc.

It is contemplated for the surveillance processor 1106 to use at leastone object classification and localization technique to identify objects1716 within the environment 1718. The identification of the objects 1716can be based on the type of surveillance and reconnaissance and the AOOor an AOI. For instance, if the vehicle 100 is being used for militarysurveillance and reconnaissance, the object classification andlocalization technique can be used to identify places in which enemypersonnel can hide (e.g., sniper nest, bunker, fighting position,vehicles located on a street, etc.). As another example, if the vehicle100 is being used for a security detail, the object classification andlocalization technique can be used to identify potential threats, suchas vehicles on a street, tanks, aircraft, defilades, etc. As anotherexample, if the vehicle 100 is being used for police surveillance andreconnaissance, the object classification and localization technique canbe used to identify personnel (criminal or hostage) in windows, behindwalls, etc.

The object classification portion of the object classification andlocalization technique can be based on computer program code havingprogram logic, control logic, or other algorithms that may or may not bebased on artificial intelligence (e.g., machine learning techniques,artificial neural network techniques, etc.). For example, thesurveillance processor 1106 can be associated with a memory that storescomputer program code having a library of objects from which thesurveillance processor 1106 uses as a comparison to identify an object1716 in the raw data 1700. For instance, the memory can have pluralimages of vehicles stored from which an object 1716 in the raw data 1700is compared with to determine that the object 1716 is a vehicle. Theplural images of vehicles can be from various angles (e.g., top view,side view, perspective view, etc.), can be of different styles ofvehicles, can be of different colors of vehicles, etc. The real timevideo stream information can be split into images by separating theframes at certain intervals. Once a frame is isolated and separated, thecomputer program code can perform object detection and classification bycausing the surveillance processor 1106 to compare the object 1716 fromthe raw data 1700 to the plural vehicles so that a statistic thatrepresents the probability that the object 1716 is a vehicle can begenerated. This statistic can be in the form of a confidence score 1800.The computer program code can cause the surveillance processor 1106 topositively identify the object 1716 as a vehicle based on a thresholdvalue of the confidence score 1800 (e.g., the surveillance processor1106 identifies an object 1716 as a vehicle if the comparison generateda match with a confidence score 1800 greater than the threshold value).

Use of a vehicle for object identification is for exemplary purposesonly, as other objects 1716 can be identified, such as persons, animals,buildings, streets, weapons, etc. In addition, other object recognitiontechniques, object size and shape recognition techniques, signalprocessing and filtration techniques (e.g., as Fourier transforms, Gabortransforms, etc.), mathematical modeling techniques, etc. can be used toidentify and track objects 1716, or a portion of an object 1716.

The surveillance processor 1106 can be configured to identify all of theobjects 1716 in the AOO or AOI, or it can be configured to identifycertain objects 1716 of interest. For instance, embodiments of theobject classification and localization technique can be used to identifyall of the vehicles on a certain street. In some embodiments, the objectclassification and localization technique can omit or remove at leastsome of the other objects 1716 (objects other than the ones identifiedas vehicles) from the distilled data 1702 so that the still imageinformation is a filtered image of the AOO or AOI.

In some embodiments, the object classification and localizationtechnique can be configured so that the identified object 1716 isincluded in the distilled data 1702 only if it has not already beenidentified earlier, or previously identified earlier within apredetermined time frame. For example, if the real time video streaminformation is captured at 30 frames per second, it may be undesirableto have 120 images of the same object 1716 over a 4 second period. Thus,a frame/time buffer can be implemented to limit duplicative displays ofthe same object 1716. For instance, the raw data 1700 can includeseveral images from several frames of the same object 1716 but atdifferent angles, but the frame/time buffer can be used to preventduplicative displays of the same object 1716 that has been captured inthis way. In an exemplary implementation, the surveillance sensor 1108can capture real time video stream information about objects 1716 in theenvironment 1718. The surveillance processor 1106 can run the real timevideo stream information through the frame/time buffer to allow thealgorithm of the object classification and localization technique toexamine each frame for object identification and localization. If anobject 1716 is identified (e.g., is matched in accordance with athreshold confidence score with learned objects) an image of the object1716 can be saved for inclusion in the distilled data 1702, which can belater transmitted by the telemetry module 1104.

Another aspect of the object classification and localization techniqueis the localization of objects 1716. The localization of objects caninvolve determining and associating coordinates to identified objects1716. For instance, the surveillance processor 1106 can determine theobjects' coordinates (e.g., longitude, latitude, altitude, gridcoordinates, etc.) and associate (or co-register) a set of coordinatesfor each identified object 1716. The coordinates for an object 1716 canbe determined via use of a GPS on-board the vehicle 100, use of areference grid map, use of optical parallax, etc. For instance, as anon-limiting, exemplary example, a GPS can be used to track the time andlocation of the vehicle 100, an optical parallax system can be used todetermine the location of objects 1716 relative to the vehicle 100, andthese locations can be compared to a reference grid of a map of the AOOor AOI to generate a set of coordinates for each identified object 1716.Additional optical systems, such as range finders for example, can beused. In some embodiments, the coordinates for each identified object1716 can be included with the distilled data 1702.

In some embodiments, the method of using a vehicle 100 can involvereceiving the raw data 1700 at a first data bandwidth 1706, andtransmitting the distilled data 1702 at a second data bandwidth 1708,the second data bandwidth 1708 being less than the first data bandwidth1706. Some embodiments, can involve the vehicle 100 transmitting thedistilled data 1702 to a computer device 1712 for further analysis orfurther or review or further analysis or further processing. It iscontemplated for the data bandwidth requirements to transmit thedistilled data 1702 to be low so as to obviate the need to establish afast connection between the vehicle 100 and the computer device 1712 viathe communications network 1710 that would otherwise be needed if thecomputations were performed by the computer device 1712. For instance,the surveillance processor 1106 can be configured to perform the heavycomputations and data analytics for collecting the raw data 1700 andtransforming it to the distilled data 1702 before the distilled data1702 is transmitted to the computer device 1712. While the raw data 1700is received by the surveillance processor 1106, only the distilled data1702 is transmitted to the computer device 1712 for additionalprocessing and storage. This allows the majority of the data to beprocessed on-site (e.g., in the vehicle 100) via the algorithmsprogrammed into the surveillance processor 1106. In addition to loweringthe data bandwidth requirements of the second data bandwidth 1708,having the processing done at the surveillance processor 1106 ensuresthat the distilled data 1702 is generated, regardless of the operabilityof the communications network 1710 (e.g., regardless of having aninternet connection or a fast internet connection). Thus, it is possiblefor the vehicle 100 to be navigated back to the user without having totransmit the data to a computation device that would otherwise benecessary to convert the data to distilled data 1702. Once a user hasthe vehicle 100, the distilled data 1702 can be retrieved. Therefore,while it is contemplated for the vehicle 100 to transmit the distilleddata 1702 to a computer device 1712 during the surveillance andreconnaissance, the vehicle 100 can be optionally operated to nottransmit the distilled data 1702 to the computer device 1712 during thesurveillance and reconnaissance. Moreover, the on-board processing ofthe surveillance processor 1106 can facilitate configuringcompatibilities of the vehicle's software with that of any computerdevice 1712. In addition, allowing the surveillance processor 1106 toperform the heavy computations and data analytics can result in thesystem operating quicker, using less computational resources, andobviate the need for an analyst to analyze the raw data 1700 andgenerate a report that would include the distilled data 1702 (i.e., theimages of the objects 1716 of interest can be generated in the distilleddata 1702 without the need for any user inputs).

In some embodiments, the method of using a vehicle can involve the firstdata bandwidth 1706 being >1 Mbps, and the second data bandwidth 1708being <1 Mbps As noted herein, the data bandwidth requirement for thefirst data bandwidth 1706 can be large to accommodate large data inputsand processing (e.g., real time video stream information about theenvironment 1718). For instance, the first data bandwidth 1706 can be >1Mbps. The data bandwidth requirement for the second data bandwidth 1708can be small to accommodate small data inputs and processing. Forinstance, the second data bandwidth 1708 can be <1 Mbps.

In some embodiments the payload housing 200 includes plural payloadhousings having a first payload housing 200 and a second payload housing200, wherein the method of using the vehicle 100 involves manuallysecuring the first payload housing 200 via the at least one interlockingarrangement 308, manually removing the first payload housing 200 todisengage the at least one interlocking arrangement 308, and manuallysecuring the second payload housing 200 via the at least oneinterlocking arrangement 308. As noted herein, components of the vehicle100 can be removed, replaced, and/or interchanged easily and quickly viathe interlocking arrangements 308. This provides for a system withmodular components that can be assembled and dis-assembled forre-configuration in a simple and efficient manner. This can be done toconfigure and re-configure the vehicle 100 to meet different operationalcriteria, thereby allowing a user to adjust the functionality of thevehicle's 100 surveillance based on the mission criteria, which canimprove the versatility of the vehicle 100.

In some embodiments, the method of using the vehicle 100 can involvereceiving first raw data 1700, manually removing a first payload housing200 to disengage the at least one interlocking arrangement 308, manuallysecuring a second payload housing 200 via the at least one interlockingarrangement 308, and receiving second raw data 1700, wherein the firstraw data 1700 is different from the second raw data 1700. The firstpayload housing 200 can include a first surveillance sensor 1108configured to receive first raw data 1700 in the form of geologicalsurvey information, whereas the second payload housing 200 can include asecond surveillance sensor 1108 configured to receive second raw data1700 in the form of identifying hostiles in an area. This demonstratesthe versatility of the system.

In some embodiments, the method of using the vehicle 100 can involvereceiving raw data 1700 and transmitting first distilled data 1702,manually removing a first payload housing 200 to disengage the at leastone interlocking arrangement 308, manually securing a second payloadhousing 200 via the at least one interlocking arrangement 308, andreceiving raw data 1700 and transmitting second distilled data 1702,wherein the first distilled data 1702 is different from the seconddistilled data 1700. The first payload housing 200 can include a firstsurveillance processor 1106 configured to receive raw data 1700 about anenvironment 1718 and generate first raw data 1700 that identifies placesin which enemy personnel can hide, whereas the second payload housing200 can include a second surveillance processor 1106 configured toreceive the same raw data 1700 about an environment 1718 and generatesecond distilled data that identifies potential threats (e.g., certaintypes of vehicles). This again demonstrates the versatility of thesystem.

Referring to FIGS. 11-16, an operating module 202 for a vehicle 100 caninclude a navigation module 1102 including a navigation processor 1110and a navigation sensor 1112 (or at least one navigation sensor 1112),the navigation module 1102 configured to communicate with a motor 110(or at least one motor 110) of the vehicle 100 to facilitate navigationand propulsion of the vehicle 100. The navigation module 1102 can be anavionics module for auto-piloting or semi-auto-piloting the vehicle 100(e.g., it can include flight control logic to fly, stabilize, andnavigate the vehicle). As a non-limiting, exemplary embodiment, thenavigation module 1102 can be a Pixhawk 4, with a 32-bit ARM cortex M4core with FPU navigation processor 1110 and at least one navigationsensor 1112 (e.g., MPU6000 accelerometer and gyroscope, a ST Micro16-bit gyroscope, a ST Micro 14-bit accelerometer/compass magnetometer,a EAS barometer, etc.). Additional navigation sensors 1112 can beincludes gyroscopes, accelerometers, barometric pressure sensors asrequired for inertial navigation inputs for a control system, etc. Othertypes of the navigation modules 1102 can be used.

The operating module 202 can include a surveillance module 1100including a surveillance processor 1106 and a surveillance sensor 1108(or at least one surveillance sensor 1108), the surveillance module 1100configured to: receive raw data, the raw data 1700 including real timevideo stream information about an environment 1718; and generatedistilled data 1702, the distilled data 1702 including still imageinformation from the real time video stream information, the still imageinformation including at least one object identified via an objectclassification and localization technique. As a non-limiting, exemplaryembodiment, the surveillance module 1100 can be a Jetson/J120, with aJetson TX2 surveillance processor 1106 with a surveillance sensor 1108(e.g., stereo camera, GPS, etc.). Other types of the surveillancemodules 1100 can be used.

The operating module 202 can include a telemetry module 1104 including atelemetry processor 1114 and a telemetry transceiver 1116, the telemetrymodule 1104 configured to transmit the distilled data 1702 to a computerdevice 1712. As a non-limiting, exemplary embodiment, the telemetrymodule 1104 can be a 433 MHz PixHawk Ardupilot telemetry kit. Othertypes of the telemetry modules 1104 can be used. It is contemplated forthe telemetry transmissions to be encrypted and transmitted via secureEM spectrum communication methods so as to provide a burst of distilleddata 1702 (e.g., a final intelligence product) to the computer device1712.

As noted above, the distilled data 1702 can include coordinates forobjects 1716, thermal signature information, time, apparent motion of anobject of interest, chemical/biological or other environmental andparticulate information, etc. Any of these data can be combined with thetelemetry data.

In some embodiments, the navigation module 1102 includes a GPS sensor.While the navigation module 1102 can include a GPS sensor, embodimentsof the vehicle 100 can be configured to operate in a GPS denied/degradedenvironment. This can be achieved via sensor fusion and other artificialintelligence techniques to allow the navigation module 1102 to navigatethe vehicle 100 without the GPS. For instance, the navigation module1102 can include inertial sensors, optical flow sensors, range finders(e.g., laser or LIDAR), infrared cameras, sound or ultrasonic sensors,etc. The data from these sensors can be processed by the navigationprocessor 1110 to make statistical inferences about location, speed,velocity vectors, altitude, etc., which can then be used for navigation.

In some embodiments, the surveillance module 1100 includes a GraphicsProcessing Unit (GPU) as the surveillance processor 1106. The GPU can beconfigured to rapidly manipulate and alter memory to accelerate thecreation of images in a frame buffer before generating the output.

In some embodiments, the telemetry module 1104 includes a gatewaytransceiver.

FIG. 11 shows an exemplary system schematic for an embodiment of thevehicle 100. The vehicle 100 system can include a power management board(PMB) 1124, which may include an adjustable-thermal fixed-magneticcircuit breaker (FMU) 1126. The PMB 1124 can be in connection with abattery 1118 (e.g., 14.8 V battery) and a universal battery eliminationcircuit (UBEC) 1122. The surveillance module 1100 can be in connectionwith the PMB 1124 and the battery 1118 and/or UBEC 1122. Thesurveillance module 1100 can be equipped with a transmitter 1120 and atleast one surveillance sensor 1108 (e.g., a visible spectrum camera, aninfrared camera, a sound sensor, etc.). Any one or combination of thesurveillance sensors 1108 can be connected to the surveillance processor1106 or the PMB 1124. The navigation module 1102 can include anavigation processor 1110 in connection with the PMB. The navigationmodule 1102 can have a navigation sensor 1112 connected to thenavigation processor 1110. The telemetry module 1104 can include atelemetry processor 1114 in connection with the navigation processor1110. The telemetry module 1104 can have a transceiver 1116 inconnection with the telemetry processor 1114 and/or the navigationprocessor 1110. The FMU 1126 can include at least one input/output (I/O)device 1128. Each I/O device 1128 can provide electrical communicationbetween the PMB 1124 an electronic speed control circuit (ESCC) 1130.Each individual ESCC 1130 can be connected to an individual motor 110via an individual pin connector 1132.

Referring to FIG. 17, some embodiments can include a communicationsnetwork 1710 configured to facilitate communication between thetelemetry module 1104 and the computer device 1712, wherein: thesurveillance module 1100 is configured to receive the raw data 1700 at afirst data bandwidth 1706; and the telemetry module 1104 is configuredto transmit the distilled data 1702 at a second data bandwidth 1708. Insome embodiments, the vehicle 100 can be part of or in connection with acommunications network 1710. For example, the telemetry module 1104 caninclude switches, transmitters, transceivers, routers, gateways, etc. tofacilitate communications via a communication protocol that facilitatescontrolled and coordinated signal transmission and processing. Thecommunication links can be established by communication protocols thatallow vehicle 100 to form a communication interface. The communicationinterface can be configured to allow the vehicle 100 (e.g., thetelemetry module 1104) and another device (e.g., the computer device1712) to form a communications network 1710. The communications network1710 can be configured as a long range wired or a wireless network, suchas an Ethernet, telephone, Wi-Fi, Bluetooth, wireless protocol,cellular, satellite network, cloud computing network, etc. Embodimentsof the communications network 1710 can be configured as a predeterminednetwork topology. This can include a mesh network topology, apoint-to-point network topology, a ring (or peer-to-peer) networktopology, a star (point-to-multiple) network topology, or anycombination thereof.

In some embodiments, the computer device 1712 can be configured tocommunicate with a control processor (e.g., chip, expansion card,microcontroller, PID controller, etc.) associated with a module 202,1100, 1102, 1104 of the vehicle 100 and to facilitate data transmissionsbetween the computer device 1712 and at least one module 202, 1100,1102, 1104, of the vehicle 100. In addition, any of the components ofthe vehicle 100 can have an application programming interface (API)and/or other interface configured to facilitate the computer device 1712that is in communication with the vehicle 100 executing commands andcontrolling aspects of the vehicle 100. Embodiments of the computerdevice 1712 can be programmed to generate a user interface configured tofacilitate control of and display of various operational aspects of thevehicle 100.

In some embodiments, the first data bandwidth 1706 is >1 Mbps, and thesecond data bandwidth 1708 is <1 Mbps.

Referring to FIG. 18-19, in some embodiments, the surveillance module1100 is configured to use machine learning as part of the objectclassification and localization technique, the machine learninggenerating a confidence score 1800 for each identified object 1716, theconfidence score 1800 being a probabilistic measure of the identifiedobject falling within a match parameter of a learned object. As notedherein, the surveillance processor 1106 can be associated with a memorythat stores computer program code having a library of objects from whichthe surveillance processor 1106 uses as a comparison to identify anobject 1716 in the raw data 1700, and the computer program code cancause the surveillance processor 1106 to positively identify the object1716 (e.g., identify it as a vehicle for example) based on a thresholdvalue of the confidence score 1800. The matched parameter used in theobject classification and localization technique can be the shape, size,location, etc. of the object that falls within the learned shapes,sizes, locations, etc. of a vehicle.

In some embodiments, the surveillance module 1100 is configured toinclude the identified object 1716 with the still image information onlywhen the confidence score is >80% or some selectable or configurablethreshold as determined by a user. The object classification andlocalization technique can omit or remove at least some objects 1716(objects other than the ones identified as vehicles) from the distilleddata 1702 so that the still image information is a filtered image of theAOO or AOI. In addition, or in the alternative, the objectclassification and localization technique can only identify objects thathave a confidence score 1800 greater than a threshold value, andotherwise does not identify them, but still generates an image of theobject 1716 (identified or not) to include in the distilled data 1702.

In some embodiments, the surveillance module 1100 is configured todisplay the confidence score 1800 associated with each identified object1716 within the distilled data 1702. For example, the virtual printoutforming a file of the image of the environment 1718 can include eachidentified object 1716 with its associated confidence score 1800juxtaposed with the object 1716.

In some embodiments, the surveillance module 1100 is configured toconvert the still image information into a Portable Document Format(PDF) file or another file format. For instance, the virtual printoutfile can be in PDF format, XML format, RTF format, DOC format, RTFformat, etc.

In some embodiments, the navigation module 1102 is configured togenerate vehicle 100 coordinates and the surveillance module 1100 isconfigured to use the vehicle 100 coordinates and a ranging technique togenerate object coordinates for the at least one identified object. Forinstance, a GPS of the navigation module 1102 can be used to track thetime and location of the vehicle 100, and a laser range finder can beused to determine the location (e.g., via optical triangulation, etc.)of objects 1716 relative to the vehicle 100.

In some embodiments, the navigation module 1102 is configured fornavigation and propulsion of an autonomous vehicle 100. As noted herein,embodiments of the vehicle 100 can be configured to be operated remotelyby a user, autonomously, or semi-autonomously.

A method of surveillance can involve receiving raw data 1700 at a firstdata bandwidth 1706, the raw data 1700 including real time video streaminformation about an environment 1718.

The method of surveillance can involve generating distilled data 1702,the distilled data 1702 including still image information from the realtime video stream information, the still image information including atleast one object 1716 identified via an object classification andlocalization technique.

The method of surveillance can involve transmitting the distilled data1702 at a second data bandwidth 1708, the first data bandwidth 1706being greater than the second data bandwidth 1708.

In some embodiments, the method of surveillance can involve the firstdata bandwidth 1706 being >1 Mbps, and the second data bandwidth 1708being <1 Mbps.

In some embodiments, the object classification and localizationtechnique involves machine learning to generate a confidence score 1800for each identified object 1716, the confidence score 1800 being aprobabilistic measure of the identified object 1716 falling within amatch parameter of a learned object.

In some embodiments, the method of surveillance can involve includingthe identified object 1716 with the distilled data only when theconfidence score 1800 is >80% or some selectable or configurablethreshold as determined by a user.

In some embodiments, the method of surveillance can involve displayingthe confidence score 1800 associated with each identified object 1716within the distilled data 1702.

In some embodiments, generating the distilled data 1702 involvesconverting the still image information into a Portable Document Format(PDF) file or another file format.

An operating module 202 for a vehicle can include a navigation module1102 including a navigation processor 1110 and a navigation sensor 1112,the navigation module 1102 configured to communicate with a motor 110(or at least one motor 110) of the vehicle 100 for navigation andpropulsion of the vehicle 100.

The operating module 202 for a vehicle 100 can include a surveillancemodule 1100 including a surveillance processor 1106 and a surveillancesensor 1108, the surveillance module 1100 configured to: receive rawdata 1700, the raw data 1700 including real time video streaminformation about an environment 1718; and process the raw data 1700 togenerate distilled data 1702, the distilled data 1702 including a stillimage information from the real time video stream information, the stillimage information including at least one object 1716 identified via anobject classification and localization technique.

The operating module 202 for a vehicle 100 can include a telemetrymodule 1104 including a telemetry processor 1114 and a telemetrytransceiver 1116, the telemetry module 1104 configured to transmit thedistilled data 1702 to a computer device 1712.

In some embodiments, the navigation module 1102 generates vehicle 100coordinates and the surveillance module 1100 uses the vehicle 100coordinates and a ranging technique to generate object coordinates forthe at least one object 1716.

In some embodiments, the surveillance module 1100 co-registers theobject coordinates with the at least one object 1716 and includes theco-register object coordinates as part of the distilled data 1702.

In some embodiments, the navigation module 1102 includes a GPS sensor.

In some embodiments, the surveillance module 1100 includes a GraphicsProcessing Unit (GPU) processor.

In some embodiments, the telemetry module 1104 includes a gatewaytransceiver.

Some embodiments can include a communications network 1710 configured tofacilitate communication between the telemetry module 1104 and thecomputer device 1712, wherein: the surveillance module 1100 isconfigured to receive the raw data 1700 at a data bandwidth of >1 Mbps;and the telemetry module 1104 is configured to transmit the distilleddata 1702 at a data bandwidth of <1 Mbps.

In some embodiments, the surveillance module 1100 is configured to usemachine learning as part of the object classification and localizationtechnique, the machine learning generating a confidence score 1800 foreach identified object 1716 that is a probabilistic measure of theidentified object 1716 falling within a match parameter of a learnedobject.

In some embodiments, the surveillance module 1100 is configured toinclude the identified object 1716 with the distilled data 1702 onlywhen the confidence score is >80% or some selectable or configurablethreshold as determined by a user.

In some embodiments, the surveillance module 1100 is configured todisplay the confidence score 1800 associated with each identified objectwithin the distilled data 1702.

In some embodiments, the surveillance module 1100 is configured toconvert the distilled data 1702 into a Portable Document Format (PDF)file or another file format.

In some embodiments, the navigation module 1102 is configured fornavigation and propulsion of an autonomous vehicle 100.

A method of surveillance can involve receiving raw data 1700 at a firstdata bandwidth 1706, the raw data 1700 including real time video streaminformation about an environment 1718.

The method of surveillance can involve generating distilled data 1702from the raw data 1700, the distilled data 1702 including a still imageinformation from the real time video stream information, the still imageinformation including at least one object 1716 identified via an objectclassification and localization technique.

The method of surveillance can involve co-registering object coordinatesfor the at least one identified object as part of the distilled data1702.

The method of surveillance can involve transmitting distilled data 1702at a second data bandwidth 1708.

The method of surveillance can involve the first data bandwidth 1706being >1 Mbps, and the second data bandwidth 1708 being <1 Mbps.

In some embodiments, the object classification and localizationtechnique involves machine learning to generate a confidence score 1800for each identified object 1716, the confidence score 1800 being aprobabilistic measure of the identified object 1716 falling within amatch parameter of a learned object.

The method of surveillance can involve including the identified theobject 1716 with the distilled data 1702 only when the confidence score1800 is >80% or some selectable or configurable threshold as determinedby a user.

The method of surveillance can involve displaying the confidence score1800 associated with each identified object within the distilled data1702.

The method of surveillance can involve generating the distilled data1702 involves converting the still image information into a PortableDocument Format (PDF) file or another file format.

Embodiments of the method disclosed herein can provide a platform for avehicle 100 that can be made in an inexpensive and quick manner, usingadditive manufacturing capabilities. With the use of FEA, build filesfor the additive manufacturing apparatus 1714 can be made to generatevehicle designs having limited number of parts and that do not requireany tools for assembly. This can allow the vehicle 100 to be assembledby a single person in less than four minutes. In addition, embodimentsof the vehicle 100 can be fabricated to make disposable component parts,which can save dedicated storage space (e.g., a user does not have tocarry already-made spare and replacement parts on his/her person) andprovide convenient, print-on-demand replacement parts. In addition,embodiments of the vehicle 100 can allow for faster and easiermaintenance (comparable to known systems). For example, a damaged arm104 can be replaced without tools in less than 30 seconds.

Use of additive manufacturing for fuselage components of an unmannedaerial vehicle 100 can reduce the logistics required for spare partssince replacement parts can be manufactured one the spot in forwarddeployed locations (e.g., locations that would otherwise requiresignificant time, resources, and logistical support to supply spareparts). The design of the vehicle 100 can be modular to allow formultiple payload packages that can be carried by different replaceablepayload housings 200. This can be used to meet different missionscenarios in real-time. Additionally, this allows for compact packagingto support soldiers transporting the system, as the vehicle 100 does notrequire tools for assembly. This again reduces the logistics that wouldotherwise be required for special tools and test equipment.

Some embodiments can provide an unmanned aerial vehicle 100 that weighsat little as five pounds and takes up less than 420 cubic inches ofspace (when assembled), and even less space when disassembled. Whenassembled, the vehicle 100 can occupy one tenth the space of standardU.S. Army ruck-sack.

Embodiments of the vehicle 100 can be designed for autonomous flightregimes, which can reduce the user's workload during operations. In someembodiments, the vehicle 100 can include onboard intelligence collectionand analysis using computer vision and machine learning technologies andalgorithms. This eliminates the need to stream full motion video back toground stations (e.g., back to the computer device 1712) for furtheranalysis and processing, reducing the time, resource, and spectrumbandwidth requirements by orders of magnitude from known unmannedintelligence, surveillance, and reconnaissance applications.

The on-board processing of the surveillance processor 1106 allows forthe software used by the operating module 202 to be highly customizable,which can allow the user to focus of the surveillance on predeterminedobjects 1716 rather than spending time and resources looking through andanalyzing all of the objects 1716 captured by each frame. For example,the user can choose to focus on information such as the presence ofenemy tanks or sniper nests in broken windows. In addition to savingtime, the bandwidth required to send information is also greatlydecreased, since only targeted images are sent to the computer device1712 instead of a live, full-motion video. The machine learningcapabilities of the vehicle 100 can decrease the time and effort ittakes the user (or the computer device 1712) to receive and analyzeintel by pushing the collection and processing of the intel onboard theoperating module 202 rather than having the user pull the data to theirlocation (e.g., the computer device 1712).

Some embodiments of the vehicle 100 can have a body 102 including atleast one mount 112, each mount 112 configured to secure a motor 110.For instance, the body 102 may not be configured to have a body cavity306.

The vehicle 100 can have a payload including at least one operatingmodule 202 for the vehicle 100. For instance, the vehicle 100 may notinclude a payload housing 200.

The vehicle 100 can include at least one interlocking arrangement 308configured to removably secure the payload to the body 102. For example,the payload can have a corresponding interlocking arrangement 308 and/ora structural formation (configured to engage the interlockingarrangement 308) to facilitate securing the payload to the body 102.

The body 102 can be structured with additive manufactured material.

Each mount 112 can be disposed in or on a structure extending from thebody 102 and/or removably attached to the body 102.

The structure can include any one or combination of: a pillaredstructure, a tripod structure, a crossbar structure, a pyramidstructure, and an arm 104. For instance, the body 102 can have at leastone pillar, tripod, or pyramid structure extending from a surface of thebody 102. Other shaped structured can be used. The mounts 112 can bedisposed in or on any one or combination of these structures. As anotherexample, the body 102 can have risers, pillars, sidewalls 302, etc.extending from a surface of the body 102 that are connected by acrossbar. The mounts 112 can be disposed in or on the crossbar.

In some embodiments, the structure is configured to extend orthogonallyor non-orthogonally from a top of the body 102, orthogonally ornon-orthogonally from a bottom of the body 102, and/or orthogonally ornon-orthogonally from a side of the body 102. This can be done tofacilitate supporting the motors 110 (attached to the mounts 112) in amanner that is conducive for the type of propulsion used by the vehicle100.

In some embodiments, the structure is configured as an arm 104 and theat least one interlocking arrangement 308 is configured to removablysecure the arm 104 to the body 102.

In some embodiments, the structure includes a hinged joint. The hingedjoint can be a barrel hinge, pivot hinge, spring hinge, a socket andpinion joint, etc.

In some embodiments, the structure is pivoted about the hinged joint totransition the structure to and from a stowed position and a deployedposition. For instance, the structure can include a first structuremember hingedly connected to a second structure member. The firststructure member can be attached to the body 102 via the interlockingarrangement 308. The second structure member can be configured to havethe mount 112. Either the first structure member or the second structuremember can have a channel that is sized and shaped to receive the otherstructure member. For instance, the first structure member has a channelthat is sized and shaped to receive the second structure member so thatwhen the second structure member is rotated about the hinged joint thefirst structure member receives the second structure member. When thesecond structure member is received within the first structure member,this can form the stowed position. When then second structure member isextended out from the channel of the first structure member, this canform the deployed position. A locking mechanism (e.g., a locking tab, aslide pin, a pin and detent feature, etc.) can be used to selectivelylock the structure in the stowed and/or deployed position.

As another example, the body 102 can have the channel or a sleeveconfigured to receive the second structure member. The second structuremember can be rotated about the hinged joint so that the channel orsleeve of the body 102 receives the second structure member. When thesecond structure member is received within the channel or sleeve, thiscan form the stowed position. When then second structure member isextended out from the channel or sleeve, this can form the deployedposition. Again, a locking mechanism can be used to selectively lock thestructure in the stowed and/or deployed position.

Transitioning the structures to and from the stowed and deployedpositions can allow a user to compact the vehicle 100 so as to occupy asmaller volume of space (e.g., when in the stowed position) and expandthe vehicle 100 when ready for operational use (e.g., when in thedeployed position).

In some embodiments, the body 102 can be configured as any one orcombination of: a walled member having a body cavity 306 formed withinthe body 102, the body cavity 306 being configured to receive thepayload; a single planar member configured to support the payload on asurface thereof; and plural planar members configured to retain thepayload by sandwiching the payload. Embodiments of the walled member(e.g., the body 102 having sidewalls 302) are described above.

The body 102 being formed as a single planar member can include aninterlocking arrangement 308 disposed in or on a surface of the singleplanar member to facilitate securement of the payload, payload housing200, and or arm 104.

The body 102 being formed as plural planar members can include aninterlocking arrangement 308 disposed in or on a surface of any one orcombination of planar members to facilitate securement of the payload,the payload housing 200, and/or the arm 104. In one embodiment, theplural planar members can include a first planar member and a secondplanar member. The first planar member can have an interlockingarrangement 308 to facilitate securement of the second planar member,the payload, payload housing 200, and/or the arm 104. The second planarmember can have an interlocking arrangement 308 to facilitate securementof the first planar member, the payload, payload housing 200, and/or thearm 104. As a non-limiting, example, the first planar member can have aninterlocking arrangement 308 to facilitate securement of the payloadand/or payload housing 200. An additional interlocking arrangement 308can be disposed on the first planar member to facilitate securement ofthe second planar member so that the second planar member sandwiches thepayload and/or payload housing 200.

In some embodiments, the motor 110 is configured to drive a propulsionmeans for the vehicle 100. The propulsion means can include any one orcombination of an impeller, a propeller 802, a thruster, and adrivetrain. As noted above, the vehicle 100 can be configured as anaerial vehicle, a land vehicle, water vehicle, and/or space vehicle. Ifthe vehicle 100 is intended for use as a land vehicle, the propulsionmeans may be a drivetrain. If the vehicle 100 is intended for use as awater vehicle, the propulsion means may be an impeller or thruster. Ifthe vehicle 100 is intended for use as an aerial vehicle, the propulsionmeans may be a propeller. If the vehicle 100 is intended for use as aspace vehicle, the propulsion means may be a thruster.

A method of producing a vehicle 100 can involve generating a body 102via additive manufacturing. The method can involve generating a payloadincluding at least one operating module 202 for the vehicle 100. Atleast one interlocking arrangement 308 can be included in or on the body102 and be configured to removably secure the payload to the body 102 bymanual assembly. The term manual assembly used herein includes assemblyvia a tool-less fashion (e.g., without the use of tools).

The method can involve generating at least one structure via additivemanufacturing with a mount 112 disposed therein or thereon. The mount112 can be configured to secure a motor 110.

The method can involve generating the structure so as to be removablysecured to the body 102 via at least one interlocking arrangement 308.

The method can involve generating a payload housing 200 via additivemanufacturing. The payload housing 200 can be configured to retain thepayload and be configured to be removably secured to the body 102 via atleast one interlocking arrangement 308.

In at least one embodiment, the method can involve generating at leastone structure via additive manufacturing with a mount 112 disposedtherein or thereon, the mount 112 being configured to secure a motor110. In addition, at least one structure can be removably secured to thebody 102 via at least one interlocking arrangement 308. The method caninvolve generating a payload housing 200 via additive manufacturing, thepayload housing 200 being configured to retain the payload andconfigured to be removably secured to the body 102 via at least oneinterlocking arrangement 308.

In some embodiments, the method can involve any one or combination ofthe body 102, the structure, and the payload housing 200 being generatedvia additive manufacturing performed at a first location and/or a secondlocation. The first location can be a manufacturing facility. The secondlocation can be an area at or near an environment 1718 within which thevehicle 100 will be operated. For instance, a first additivemanufacturing apparatus 1714 can be located at the first location and asecond additive manufacturing apparatus 1714 can be located at thesecond location. Being near the environment 1718 can include beingwithin operational reach of the environment 1718 (e.g., the vehicle 100can be navigated to the environment 1718 from the second location andstill have enough power to allow it to effectively perform its intendedfunction and still be within range so as to allow for telecommunicationbetween it and the computer device 1712). None, some, or all of thecomponent parts of the vehicle 100 can be fabricated using the firstadditive manufacturing apparatus 1714, while none, some or allcomponents are fabricated using the first additive manufacturingapparatus 1714. The determination of which components are made using thefirst additive manufacturing apparatus 1714 and which component partsare made using the second additive manufacturing apparatus 1714 can bebased on the intended use of the vehicle 100 and the environmentalconstraints associated with that use. For instance, the vehicle 100 maybe intended to use by a soldier in the field to gather intelligenceabout the environment 1718. The soldier may have to carry the componentsof the vehicle 100 and/or the second additive manufacturing apparatus1714 to the second location. Factors of: a) the burden of carrying theequipment; b) the ability and speed with which the second additivemanufacturing apparatus 1714 can fabricate component parts; c) missionconstraints (e.g., operational security, weather conditions, etc.); etc.will dictate which component parts are made using the first additivemanufacturing apparatus 1714 and which component parts are made usingthe second additive manufacturing apparatus 1714.

If any of the components becomes damaged or requires re-design, any ofthe components can be fabricated for such purposes using any one orcombination of the first additive manufacturing apparatus 1714 and thesecond additive manufacturing apparatus 1714.

The method can involve determining, via Finite Element Analysis (“FEA”),design criteria (e.g., shape and configuration) of any one orcombination of the body 102, the structure, and the payload housing 200.

In some embodiments, the FEA uses operational parameters related to atype of propulsion for which the motor 110 is configured, a type ofsurveillance for which the operating module 202 is configured, and/orenvironmental constraints (e.g., weather conditions, atmosphericaltitude, water depth, pressure conditions, temperature conditions,chemical exposure conditions, radiation exposure conditions, lightexposure conditions, low earth orbit conditions, other planetaryconditions, outer-space conditions, etc.) within which the vehicle 100will be operated.

In some embodiments, the environmental constraints include any one orcombination of: transport of the second additive manufacturing apparatus1712 and/or components of the vehicle 100 to the second location. Thecomponents can include the body 102, the structure, the payload, thepayload housing 200, raw material for the build, the motor 110, abattery unit, circuitry, sensors, propulsion means (e.g., an impeller, apropeller 802, a thruster, a drivetrain, etc.), and ability and speedwith which the additive manufacturing at the second location generatescomponents of the vehicle 100.

It will be understood that modifications to the embodiments disclosedherein can be made to meet a particular set of design criteria. Forinstance, any of vehicles 100, operating modules 202, surveillancemodules 1100, navigation modules 1102, telemetry modules 1104,communications network 1710 components, body portions 102, arm portions104, payload housing portions 200, motors 110, or any other componentcan be any suitable number or type of each to meet a particularobjective. Therefore, while certain exemplary embodiments of the vehicle100 and methods of using the same disclosed herein have been discussedand illustrated, it is to be distinctly understood that the invention isnot limited thereto but can be otherwise variously embodied andpracticed within the scope of the following claims.

It will be appreciated that some components, features, and/orconfigurations can be described in connection with only one particularembodiment, but these same components, features, and/or configurationscan be applied or used with many other embodiments and should beconsidered applicable to the other embodiments, unless stated otherwiseor unless such a component, feature, and/or configuration is technicallyimpossible to use with the other embodiment. Thus, the components,features, and/or configurations of the various embodiments can becombined together in any manner and such combinations are expresslycontemplated and disclosed by this statement.

It will be appreciated by those skilled in the art that the presentinvention can be embodied in other specific forms without departing fromthe spirit or essential characteristics thereof. The presently disclosedembodiments are therefore considered in all respects to be illustrativeand not restricted. The scope of the invention is indicated by theappended claims rather than the foregoing description and all changesthat come within the meaning and range and equivalence thereof areintended to be embraced therein. Additionally, the disclosure of a rangeof values is a disclosure of every numerical value within that range,including the end points.

What is claimed is:
 1. A vehicle, comprising: a body having a bodybottom conjoined with a body sidewall and a body top forming a bodycavity, wherein the body top includes a body top opening and the bodysidewall includes a body sidewall opening; a payload housing having apayload bottom conjoined with a payload housing sidewall and a payloadhousing top forming a payload housing cavity, wherein the payloadhousing cavity is configured to hold at least one operating module forthe vehicle; at least one arm; and at least one interlocking arrangementof the body top opening or body side wall configured to removably securethe payload housing and the at least one arm to the body; wherein eachof the body, the payload housing, and the at least one arm arestructured with additive manufactured material.
 2. The vehicle recitedin claim 1, wherein each of the body, the payload housing, and the atleast one arm are structured entirely with additive manufacturedmaterial.
 3. The vehicle recited in claim 1, comprising: a coverstructured with additive manufactured material, wherein the at least oneinterlocking arrangement is configured to removably secure the cover tothe body.
 4. The vehicle recited in claim 1, wherein the at least oneinterlocking arrangement is configured to be manually transitionedbetween an engaged configuration and a disengaged configuration.
 5. Thevehicle recited in claim 1, wherein the at least one arm includes pluralarms.
 6. The vehicle recited in claim 1, wherein the at least one armincludes a failure point configured to facilitate mechanical failure ofthe at least one arm upon experiencing a threshold force vector beforetransferring the threshold force vector to another component of thevehicle.
 7. The vehicle recited in claim 1, wherein the at least one armincludes at least one motor configured to propel the vehicle.
 8. Thevehicle recited in claim 7, wherein the at least one arm includes anelectrical connector conduit configured to route an electrical connectorfrom the at least one motor to facilitate electrical communicationbetween the motor and the at least one operating module.
 9. The vehiclerecited in claim 1, wherein the vehicle is configured to be an aerialvehicle, a land vehicle, and/or a water vehicle.
 10. The vehicle recitedin claim 1, wherein the vehicle is configured to be an autonomousvehicle.
 11. The vehicle recited in claim 1, wherein the at least oneoperating module includes a navigation module, a surveillance module,and/or a telemetry module.
 12. The vehicle recited in claim 11, whereinthe navigation module is an avionics module.
 13. A method of using avehicle, the method comprising: manually assembling a payload housingand at least one arm to a body via at least interlocking arrangementused to secure the payload housing to the body, and the at least one armto the body; and manually attaching at least one motor to the at leastone arm.
 14. The method recited in claim 13, comprising: fabricating thebody, the payload housing, and the at least one arm via additivemanufacturing.
 15. The method recited in claim 13, comprising: receivingraw data including real time video stream information about anenvironment; and generating distilled data including still imageinformation from the real time video stream information, the still imageinformation including at least one object identified via an objectclassification and localization technique.
 16. The method recited inclaim 15, comprising: receiving the raw data at a first data bandwidth;and transmitting the distilled data at a second data bandwidth, thesecond data bandwidth being less than the first data bandwidth.
 17. Themethod recited in claim 16, wherein: the first data bandwidth is >1Mbps; and the second data bandwidth is <1 Mbps.
 18. The method recitedin claim 13, wherein the payload housing includes plural payloadhousings having a first payload housing and a second payload housing,the method comprising: manually securing the first payload housing viathe at least one interlocking arrangement; manually removing the firstpayload housing to disengage the at least one interlocking arrangement;manually securing the second payload housing via the at least oneinterlocking arrangement.
 19. The method recited in claim 15,comprising: receiving first raw data; manually removing a first payloadhousing to disengage the at least one interlocking arrangement; manuallysecuring a second payload housing via the at least one interlockingarrangement; and receiving second raw data; wherein the first raw datais different from the second raw data.
 20. The method recited in claim15, comprising: receiving raw data and transmitting first distilleddata; manually removing a first payload housing to disengage the atleast one interlocking arrangement; manually securing a second payloadhousing via the at least one interlocking arrangement; and receiving rawdata and transmitting second distilled data; wherein the first distilleddata is different from the second distilled data.
 21. An operatingmodule for a vehicle, comprising: a navigation module including anavigation processor and at least one navigation sensor, the navigationmodule configured to communicate with at least one motor of the vehicleto facilitate navigation and propulsion of the vehicle; a surveillancemodule including a surveillance processor and at least one surveillancesensor, the surveillance module configured to: receive raw data, the rawdata including real time video stream information about an environment;and generate distilled data, the distilled data including still imageinformation from the real time video stream information, the still imageinformation including at least one object identified via an objectclassification and localization technique; a telemetry module includinga telemetry processor and a telemetry transceiver, the telemetry moduleconfigured to transmit the distilled data to a computer device.
 22. Theoperating module recited in claim 21, wherein the navigation moduleincludes a Global Positioning System (GPS) sensor.
 23. The operatingmodule recited in claim 21, wherein the surveillance module includes aGraphics Processing Unit (GPU) processor.
 24. The operating modulerecited in claim 21, wherein the telemetry module includes a gatewaytransceiver.
 25. The operating module recited in claim 21, comprising: acommunications network configured to facilitate communication betweenthe telemetry module and the computer device, wherein: the surveillancemodule is configured to receive the raw data at a first data bandwidth;and the telemetry module is configured to transmit the distilled data ata second data bandwidth.
 26. The operating module recited in claim 25,wherein: the first data bandwidth is >1 Mbps; and the second databandwidth is <1 Mbps.
 27. The operating module recited in claim 21,wherein the surveillance module is configured to use machine learning aspart of the object classification and localization technique, themachine learning generating a confidence score for each identifiedobject, the confidence score being a probabilistic measure of theidentified object falling within a match parameter of a learned object.28. The operating module recited in claim 27, wherein the surveillancemodule is configured to include the identified object with the stillimage information only when the confidence score is greater than aselectable or configurable threshold.
 29. The operating module recitedin claim 27, wherein the surveillance module is configured to displaythe confidence score associated with each identified object within thedistilled data.
 30. The operating module recited in claim 21, whereinthe surveillance module is configured to convert the still imageinformation into a Portable Document Format (PDF) file or another fileformat.
 31. The operating module recited in claim 21, wherein thenavigation module is configured to generate vehicle coordinates and thesurveillance module is configured to use the vehicle coordinates and aranging technique to generate object coordinates for the at least oneidentified object.
 32. The operating module recited in claim 21, whereinthe navigation module is configured for navigation and propulsion of anautonomous vehicle.
 33. A method of surveillance, the method comprising:receiving raw data at a first data bandwidth, the raw data includingreal time video stream information about an environment; generatingdistilled data, the distilled data including still image informationfrom the real time video stream information, the still image informationincluding at least one object identified via an object classificationand localization technique; and transmitting the distilled data at asecond data bandwidth, the first data bandwidth being greater than thesecond data bandwidth.
 34. The method recited in claim 33, wherein: thefirst data bandwidth is >1 Mbps; and the second data bandwidth is <1Mbps.
 35. The method recited in claim 33, wherein the objectclassification and localization technique involves machine learning togenerate a confidence score for each identified object, the confidencescore being a probabilistic measure of the identified object fallingwithin a match parameter of a learned object.
 36. The method recited inclaim 34, comprising: including the identified object with the distilleddata only when the confidence score is greater than a selectable orconfigurable threshold.
 37. The method recited in claim 36, comprising:displaying the confidence score associated with each identified objectwithin the distilled data.
 38. The method recited in claim 33, whereingenerating the distilled data involves converting the still imageinformation into a Portable Document Format (PDF) file or another fileformat.
 39. An operating module for a vehicle, comprising: a navigationmodule including a navigation processor and at least one navigationsensor, the navigation module configured to communicate with at leastone motor of the vehicle for navigation and propulsion of the vehicle; asurveillance module including a surveillance processor and at least onesurveillance sensor, the surveillance module configured to: receive rawdata, the raw data including real time video stream information about anenvironment; and process the raw data to generate distilled data, thedistilled data including a still image information from the real timevideo stream information, the still image information including at leastone object identified via an object classification and localizationtechnique; and a telemetry module including a telemetry processor and atelemetry transceiver, the telemetry module configured to transmit thedistilled data to a computer device; wherein the navigation modulegenerates vehicle coordinates and the surveillance module uses thevehicle coordinates and a ranging technique to generate objectcoordinates for the at least one object; and wherein the surveillancemodule co-registers the object coordinates with the at least one objectand includes the co-register object coordinates as part of the distilleddata.
 40. The operating module recited in claim 39, wherein thenavigation module includes a Global Positioning System (GPS) sensor. 41.The operating module recited in claim 39, wherein the surveillancemodule includes a Graphics Processing Unit (GPU) processor.
 42. Theoperating module recited in claim 39, wherein the telemetry moduleincludes a gateway transceiver.
 43. The operating module recited inclaim 39, comprising: a communications network configured to facilitatecommunication between the telemetry module and the computer device,wherein: the surveillance module is configured to receive the raw dataat a data bandwidth of >1 Mbps; and the telemetry module is configuredto transmit the distilled data at a data bandwidth of <1 Mbps.
 44. Theoperating module recited in claim 39, wherein the surveillance module isconfigured to use machine learning as part of the object classificationand localization technique, the machine learning generating a confidencescore for each identified object that is a probabilistic measure of theidentified object falling within a match parameter of a learned object.45. The operating module recited in claim 44, wherein the surveillancemodule is configured to include the identified object with the distilleddata only when the confidence score is greater than a selectable orconfigurable threshold.
 46. The operating module recited in claim 45,wherein the surveillance module is configured to display the confidencescore associated with each identified object within the distilled data.47. The operating module recited in claim 39, wherein the surveillancemodule is configured to convert the distilled data into a PortableDocument Format (PDF) file or another file format.
 48. The operatingmodule recited in claim 39, wherein the navigation module is configuredfor navigation and propulsion of an autonomous vehicle.
 49. A method ofsurveillance, the method comprising: receiving raw data at a first adata bandwidth, the raw data including real time video streaminformation about an environment; and generating distilled data from theraw data, the distilled data including a still image information fromthe real time video stream information, the still image informationincluding at least one object identified via an object classificationand localization technique; co-registering object coordinates for the atleast one identified object as part of the distilled data; andtransmitting distilled data at a second data bandwidth.
 50. The methodrecited in claim 49, wherein: the first a data bandwidth is >1 Mbps; andthe second data bandwidth is <1 Mbps.
 51. The method recited in claim49, wherein the object classification and localization techniqueinvolves machine learning to generate a confidence score for eachidentified object, the confidence score being a probabilistic measure ofthe identified object falling within a match parameter of a learnedobject.
 52. The method recited in claim 51, comprising: including theidentified the object with the distilled data only when the confidencescore is greater than a selectable or configurable threshold.
 53. Themethod recited in claim 52, comprising: displaying the confidence scoreassociated with each identified object within the distilled data. 54.The method recited in claim 49, wherein generating the distilled datainvolves converting the still image information into a Portable DocumentFormat (PDF) file or another file format.
 55. A vehicle, comprising: abody including at least one mount, each mount configured to secure amotor; a payload including at least one operating module for thevehicle; at least one interlocking arrangement configured to removablysecure the payload to the body; wherein the body is structured withadditive manufactured material.
 56. The vehicle recited in claim 55,wherein each mount is disposed in or on a structure, the structureextending from the body and/or removably attached to the body.
 57. Thevehicle recited in claim 56, wherein the structure includes any one orcombination of: a pillared structure, a tripod structure, a crossbarstructure, a pyramid structure, and an arm.
 58. The vehicle recited inclaim 57, wherein the structure is configured to extend orthogonally ornon-orthogonally from a top of the body, orthogonally ornon-orthogonally from a bottom of the body, and/or orthogonally ornon-orthogonally from a side of the body.
 59. The vehicle recited inclaim 57, wherein the structure is configured as an arm and the at leastone interlocking arrangement is configured to removably secure the armto the body.
 60. The vehicle recited in claim 56, wherein the structureincludes a hinged joint.
 61. The vehicle recited in claim 60, whereinthe structured is pivoted about the hinged joint to transition thestructure to and from a stowed position and a deployed position.
 62. Thevehicle recited in claim 55, wherein the body is configured as any oneor combination of: a walled member having a body cavity formed withinthe body, the cavity being configured to receive the payload; a singleplanar member configured to support the payload on a surface thereof;and plural planar members configured to retain the payload bysandwiching the payload.
 63. The vehicle recited in claim 55, whereinthe motor is configured to drive a propulsion means for the vehicle. 64.The vehicle recited in claim 63, wherein the propulsion means includesany one or combination of an impeller, a propeller, a thruster, and adrivetrain.
 65. A method of producing a vehicle, the method comprising:generating a body via additive manufacturing; and generating a payloadincluding at least one operating module for the vehicle; wherein atleast one interlocking arrangement is included in or on the body and isconfigured to removably secure the payload to the body by manualassembly.
 66. The method recited in claim 65, comprising: generating atleast one structure via additive manufacturing with a mount disposedtherein or thereon, the mount configured to secure a motor.
 67. Themethod recited in claim 66, wherein the at least one structure isremovably secured to the body via the at least one interlockingarrangement.
 68. The method recited in claim 65, comprising: generatinga payload housing via additive manufacturing, the payload housingconfigured to retain the payload and configured to be removably securedto the body via the at least one interlocking arrangement.
 69. Themethod recited in claim 65, comprising: generating at least onestructure via additive manufacturing with a mount disposed therein orthereon, the mount configured to secure a motor, wherein the at leastone structure is removably secured to the body via at least oneinterlocking arrangement; and generating a payload housing via additivemanufacturing, the payload housing configured to retain the payload andconfigured to be removably secured to the body via the at least oneinterlocking arrangement.
 70. The method recited in claim 69, wherein:any one or combination of the body, the structure, and the payloadhousing is partly or entirely generated via additive manufacturingperformed at a first location and/or a second location; the firstlocation is a manufacturing facility; the second location is an area ator within operational reach of an environment within which the vehiclewill be operated.
 71. The method recited in claim 70, wherein designcriteria including shape and configuration of any one or combination ofthe body, the structure, and the payload housing is determined by FiniteElement Analysis (“FEA”).
 72. The method recited in claim 71, whereinthe FEA uses operational parameters related to a type of propulsion forwhich the motor is configured, a type of operational module for whichthe operating module is configured, and/or environmental constraintswithin which the vehicle will be operated.
 73. The method recited inclaim 72, wherein the environmental constraints include any one orcombination of: transport of components of the vehicle to the secondlocation, the components including the body, the structure, the payload,the payload housing, the motor, a battery unit, circuitry, sensors,and/or propulsion means, wherein the propulsion means includes any oneor combination of an impeller, a propeller, a thruster, and adrivetrain; and ability and speed with which the additive manufacturingat the second location generates components of the vehicle.